TY - JOUR
T1 - A multisensor intelligent device for real-time multiphase flow metering in oil fields
AU - Meribout, Mahmoud
AU - Al-Rawahi, Nabeel Z.
AU - Al-Naamany, Ahmed M.
AU - Al-Bimani, Ali
AU - Al-Busaidi, Khamis
AU - Meribout, Adel
PY - 2010/6
Y1 - 2010/6
N2 - In this paper, a new multiphase flow metering device for real-time measurement of oil, gas, and water flow rates is presented. It is composed of several electrical and acoustic sensors whose signals are digitalized and processed by a multilayer neural network. This latest uses the physical models of multiphase fluids to reduce the complexity of the parameter space while improving its accuracy. Furthermore, to overcome the uncertainties of the electrical sensors in the range of 40%-60% and above 90% water-cut (i.e., ranges where most of the multiphase flow meter fail), two rings of high- and low-frequency ultrasonic sensors are used for low and high gas fractions, respectively. The results of experiments that have been conducted in an in-house laboratory-scale multiphase flow loop show that real-time classification for up to 90% gas fraction can be achieved with less than 10% relative error.
AB - In this paper, a new multiphase flow metering device for real-time measurement of oil, gas, and water flow rates is presented. It is composed of several electrical and acoustic sensors whose signals are digitalized and processed by a multilayer neural network. This latest uses the physical models of multiphase fluids to reduce the complexity of the parameter space while improving its accuracy. Furthermore, to overcome the uncertainties of the electrical sensors in the range of 40%-60% and above 90% water-cut (i.e., ranges where most of the multiphase flow meter fail), two rings of high- and low-frequency ultrasonic sensors are used for low and high gas fractions, respectively. The results of experiments that have been conducted in an in-house laboratory-scale multiphase flow loop show that real-time classification for up to 90% gas fraction can be achieved with less than 10% relative error.
KW - Artificial intelligence
KW - Capacitance and conductance probes
KW - Embedded systems design
KW - Gas flow rate measurement
KW - Multiphase flow metering
KW - Neural network
KW - Ultrasonic waves
KW - Water-cut measurement
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U2 - 10.1109/TIM.2009.2028210
DO - 10.1109/TIM.2009.2028210
M3 - Article
AN - SCOPUS:77952291053
SN - 0018-9456
VL - 59
SP - 1507
EP - 1519
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
IS - 6
M1 - 5263016
ER -